{"record":{"id":"28bbb482f094fca1","repo":"tensorflow/models","slug":"unpool-length-is-not-supported-by-append-dense-inp","errorCode":null,"errorMessage":"unpool_length is not supported by append_dense_inputs now.","messagePattern":"unpool_length is not supported by append_dense_inputs now\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/nlp/modeling/networks/funnel_transformer.py","lineNumber":494,"sourceCode":"      mask = inputs.get('input_mask')\n      type_ids = inputs.get('input_type_ids')\n      word_embeddings = inputs.get('input_word_embeddings', None)\n\n      dense_inputs = inputs.get('dense_inputs', None)\n      dense_mask = inputs.get('dense_mask', None)\n      dense_type_ids = inputs.get('dense_type_ids', None)\n    else:\n      raise ValueError('Unexpected inputs type to %s.' % self.__class__)\n\n    if word_embeddings is None:\n      word_embeddings = self._embedding_layer(word_ids)\n\n    if dense_inputs is not None:\n      # Allow concatenation of the dense embeddings at sequence end if requested\n      # and `unpool_length`` is set as zero\n      if self._append_dense_inputs:\n        if self._unpool_length != 0:\n          raise ValueError(\n              'unpool_length is not supported by append_dense_inputs now.'\n          )\n        word_embeddings = tf.concat([word_embeddings, dense_inputs], axis=1)\n        type_ids = tf.concat([type_ids, dense_type_ids], axis=1)\n        mask = tf.concat([mask, dense_mask], axis=1)\n      else:\n        # Concat the dense embeddings at sequence begin so unpool_len can\n        # control embedding not being pooled.\n        word_embeddings = tf.concat([dense_inputs, word_embeddings], axis=1)\n        type_ids = tf.concat([dense_type_ids, type_ids], axis=1)\n        mask = tf.concat([dense_mask, mask], axis=1)\n    # absolute position embeddings\n    position_embeddings = self._position_embedding_layer(word_embeddings)\n    type_embeddings = self._type_embedding_layer(type_ids)\n\n    embeddings = tf_keras.layers.add(\n        [word_embeddings, position_embeddings, type_embeddings])\n    embeddings = self._embedding_norm_layer(embeddings)","sourceCodeStart":476,"sourceCodeEnd":512,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/nlp/modeling/networks/funnel_transformer.py#L476-L512","documentation":"Error \"unpool_length is not supported by append_dense_inputs now.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/nlp/modeling/networks/funnel_transformer.py:494 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":[],"exampleFix":null,"handlingStrategy":null,"validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"e006f5f0d534913e49c1f1dae87364039fa607e2","analyzedAt":"2026-08-24T14:09:15.576Z","schemaVersion":2},"datasetVersion":"2026-08-24T17:17:21.512Z"}